Abnormal public place sound feature extraction and recognition method

Abstract

The invention relates to an abnormal public place sound extraction and recognition method for improving extreme-point symmetric mode decomposition (ESMD), abbreviated as D-ESMD. The method is characterized in that random T distribution sequence signals are added to abnormal public place sound, thereby reducing the influence of public place background noise on abnormal sound feature extraction; aiming at the problem of poor decomposition effect of original ESMD when abnormal sound is decomposed, a method for replacing extreme midpoint odd-even interpolation with symmetric midpoint interpolation is put forward to improve the decomposition efficiency and recognition rate of abnormal sound; aiming at the defects of original ESMD on effective decomposition mode selection, a permutation entropy algorithm is put forward to detect the complexity of the mode obtained by ESMD decomposition, so that an effective mode component of abnormal sound is adaptively obtained. By using the method, the feature of abnormal sound can be sufficiently described, good class recognition results can be obtained, and the feature of abnormal sound can be accurately extracted; and the method has good robustness on environmental background noise.

Description

technical field [0001] The invention belongs to the technical field of audio signal feature extraction and pattern recognition, and in particular relates to a method for feature extraction and identification of abnormal sounds in public places. Background technique [0002] Public places such as squares, bus stations, subways, etc. have the characteristics of large flow of people and wide areas, and the safety precautions of public places have always been widely concerned by governments and people of all countries. At present, the monitoring technology mainly based on video monitoring has played a positive role in the safety of public places. However, video monitoring technology has problems such as monitoring dead spots and blurry monitoring in rainy days. As we all know, when abnormal events occur, they are often accompanied by abnormal sounds such as screams, gunshots, broken glass, explosions, etc. Therefore, the cooperative operation of audio monitoring and video monito...

AI Technical Summary

Problems solved by technology

④ When the ESMD method decomposes abnormal sound signals in public places, set the number of screening K in the interval [K min , K max ], and then use different screening times to repeatedly decompose the abnormal sound signal, and finally use the principle of least squares to calculate the optimal screening times, resulting in a long time-consuming ESMD decomposition of abnormal sound signals

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